Application Areas
34,437 papers (4 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Domain Adaptation (9,897)
Efficient Computing (8,226)
Data Augmentation (3,648)
Fairness (3,574)
Knowledge Distillation (3,219)
Privacy (3,022)
Domain Generalization (1,972)
Model Compression (1,736)
Risk Management (1,119)
Model Merging (592)
Recommender Systems (343)
Information Retrieval (249)
Text Classification (144)
Text Processing (2)
Papers per year
1
3
5
5
4
19
24
28
26
35
42
55
142
116
147
330
517
1,020
1,828
2,498
3,411
3,854
5,063
6,422
7,176
1,666
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
Uncertainty Quantification and Deep Ensembles
NeurIPS 2021
Uncertainty Reduction for Model Adaptation in Semantic Segmentation
CVPR 2021
Uncertainty Sets for Image Classifiers using Conformal Prediction
ICLR 2021
UnClE: Explicitly Leveraging Semantic Similarity to Reduce the Parameters of Word Embeddings
EMNLP 2021
Uncovering Latent Biases in Text: Method and Application to Peer Review
AAAI 2021
Uncovering Main Causalities for Long-tailed Information Extraction
EMNLP 2021
Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability
ICML 2021
Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Model
ACL 2021
Understanding and Evaluating Racial Biases in Image Captioning
ICCV 2021
Understanding and Improving Lexical Choice in Non-Autoregressive Translation
ICLR 2021
Understanding and Interpreting the Impact of User Context in Hate Speech Detection
NAACL 2021
Understanding and Mitigating Accuracy Disparity in Regression
ICML 2021
Understanding and Mitigating Annotation Bias in Facial Expression Recognition
ICCV 2021
Understanding and Overcoming the Challenges of Efficient Transformer Quantization
EMNLP 2021
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
NAACL 2021
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
ICML 2021
Understanding Instance-Level Label Noise: Disparate Impacts and Treatments
ICML 2021
Understanding Model Robustness to User-generated Noisy Texts
EMNLP 2021
Understanding Robustness of Transformers for Image Classification
ICCV 2021
Understanding the Effect of Bias in Deep Anomaly Detection
IJCAI 2021
Understanding the failure modes of out-of-distribution generalization
ICLR 2021
Understanding the Generalization Benefit of Model Invariance from a Data Perspective
NeurIPS 2021
Understanding the Impact of UGC Specificities on Translation Quality
EMNLP 2021
Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning
NeurIPS 2021
Understanding Unintended Memorization in Language Models Under Federated Learning
NAACL 2021